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We applied a true-experimental randomized control posttest design to collect and analyze quantitative and qualitative data to compare the effects of the AR and traditional board games on students’ SDG learning achievements.

We applied a true-experimental randomized control posttest design to collect and analyze quantitative and qualitative data to compare the effects of AR and traditional board games on students' SDG learning achievements.

Our analysis of the quantitative and qualitative data revealed that the effects of AR and traditional board games on the students' cognitive outcomes differed significantly, indicating the importance of providing a situated learning environment in SDG education. Moreover, the students perceived that the incorporation of the AR game into SDG learning improved their learning effectiveness – including both cognitive and affective dimensions – thus confirming its educational value and potential in SDG learning.

To the best of our knowledge, this is the first study to explore the effectiveness of different learning tools (AR and traditional board games) and to evaluate the importance of providing a situated learning environment through a true-experimental randomized control posttest design.

Existing studies reflect that traditional teaching–learning relationships between supervisors and graduate students have become disjointed with actuality seriously. In particular, there are practical difficulties in handling many students from coursework-based postgraduate degrees under current university curricula. Therefore, this study aims to explore the relationship between research supervisors and graduate students on social media, which is popular among students.

This study surveyed 109 graduate students from two majors (population around 100 each) of a university in Hong Kong to explore their information usage for research on social media, related attitudes and their perceived supervisor relationships. The differences between the two majors were also compared.

The authors’ findings indicated that graduate students were active on social media, and social media has successfully provided effective alternate ways for students to communicate with their research supervisors. Social media could improve relationships between supervisors and research students and among fellow students. Besides education purposes, students also discussed their personal affairs on social media with supervisors, demonstrating enhanced trusted relationships. Graduate students also showed confidence in the further application of social media in higher education. Some differences between respondents from the two programs were also found in terms of communication contents, strengths, personal preferences and purposes for using social media.

Scant studies focus on the relationship between supervisors and graduate students under the current social media environment, especially for students from coursework-based postgraduate degrees. At a deeper level, for the widespread use of social media in the information age, this study explores the specific changes brought about by social media. Therefore, this study is of great theoretical and practical value to graduate education under the current social media environment.

To investigate the impact of knowledge-intensive FDI in the Chinese pharmaceutical industry, this study analyzes the activity of foreign MNEs operating in this context by exploring their innovative background, the organizational arrangements they use for local knowledge creation and the performance of their local innovative processes. Based on the analysis of the universe of USPTO pharmaceutical patents applied for between 1975 and 2010 and granted to foreign assignees utilizing the work of Chinese inventors, our results show that, while the presence of foreign MNEs in the Chinese pharmaceutical industry entails a strong potential for positive externalities that could enhance the performance of the local innovation system, such externalities do not completely materialize yet, likely because of local actors’ limited absorptive capacity.

This study aims to investigate the feasibility of employing a multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation. The formulated objectives are the minimisation of the total allocation cost of the anti-fraud capacities and the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots.

From the literature survey conducted and primary qualitative data gathered from the 17 licenced banks in South Africa on fraud investigators, the suggested fraud investigators are the organisation’s finance department, the internal audit committee, the external risk manager, accountants and forensic accountants. These five human resource capacities were considered for the formulation of the multi-objectives integer programming (MOIP) model. The MOIP model is employed for the optimisation of the employed capacities for cyberfraud mitigation to ensure the effective allocation and utilisation of human resources. Thus, the MOIP model is validated by a genetic algorithm (GA) solver to obtain the Pareto-optimum solution without the violation of the identified constraints.

The formulated objective functions are optimised simultaneously. The Pareto front for the two objectives of the MOIP model comprises the set of optimal solutions, which are not dominated by any other feasible solution. These are the feasible choices, which indicate the suitability of the MOIP to achieve the set objectives.

The results obtained indicate the feasibility of simultaneously achieving the minimisation of the total allocation cost of the anti-fraud capacities, or the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots – or the trade-off between them, if they cannot be reached simultaneously. This study recommends the use of an iterative MOIP framework for decision-makers which may aid decision-making with respect to the allocation and utilisation of human resources.

The originality of this work lies in the development of multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation.

Current virtual simulation platforms provide various tools to generate non-immersive simulation processes purposefully in different domains. The generated simulation processes are adopted for analysis, presentation, demonstration and verification. In the virtual maintenance domain, this intuitive and visual method has benefitted product maintainability design and improvement. Generating an ideal and reasonable non-immersive virtual maintenance simulation is always time-consuming because of the complicated human operations and logical relationships involved. This study aims to propose a semiautomatic approach to increase efficiency in non-immersive virtual maintenance simulation implementation.

The methodology analyzes the general catalogs of common maintenance tasks and explores the corresponding secondary development approaches of simulation tools that can achieve motion simulation in virtual environments, by focusing on the diversity, complexity and uncertainty in non-immersive virtual simulation process generation. Afterward, a single virtual human motion can be generated by controlling the parameters and indices of the simulation tools. Subsequently, all of the generated single motions are connected logically to simulate the entire maintenance process.

Instead of selecting various tools, such as that in a traditional method, the proposed methodology analyzes and integrates the necessary basic parameters considering the characteristics of virtual maintenance simulation for a target maintenance activity.

The user can control the predefined parameters to generate the simulation combining several other simple operations in virtual environments. Consequently, the methodology decreases simulation tool selection and logic consideration and increases efficiency to a certain extent in non-immersive virtual maintenance simulation generation.

With the ascendance of information technology, particularly through the internet, external information sources and their impacts can be readily transferred to influence the performance of financial markets within a short period of time. The purpose of this paper is to investigate how incidents affect stock prices and volatility using vector error correction and autoregressive-generalized auto regressive conditional Heteroskedasticity models, respectively.

To characterize the investors’ responses to incidents, the authors introduce indices derived using search volumes from Google Trends and the Baidu Index.

The empirical results indicate that an outbreak of disasters can increase volatility temporarily, and exert significant negative effects on stock prices in a relatively long time. In addition, indices derived from different search engines show differentiation, with the Google Trends search index mainly representing international investors and appearing more significant and persistent.

This study contributes to the existing literature by incorporating open-source data to analyze how catastrophic events affect financial markets and effect persistence.

Product variant design can only be achieved after all its constituent parts have been implemented by variant design. It is necessary to plan the sequence of part variant design reasonably. The product variant design process involves a large amount of information transfer events at the dimensional level. A reasonable product variant design process needs to make full use of the information transfer characters of parts to decrease the uncertainty of product variant design process. The existing methods of researching the product variant design process mainly focus on resource constraint and activity logic. They are deficient, however, in information transfer resolution and uncertainty management. This paper aims to address these issues.

This paper identifies the number of dimension transfer paths and the position of dimension locating within a transfer path as being the key factors affecting the information transfer role of dimension. Information transfer utility is proposed to measure the information transfer capability of dimensions and parts. Based on these, a two-stage approach of generating the sequence of part variant design based on information transfer utility is proposed.

The uncertainty of dimension constraint network is minimal during the product variant design process when parts are implemented by variant design under the sequence generated through a two-stage method based on the information transfer utilities of parts, as does the times of parameter transferring and iteration in dimension constraint network.

Part variant design under the sequence of descending information transferring utilities can decrease the difficulty of implementing product variant design validly and also increase the efficiency. This suggests an innovative method to planning the product variant design process reasonably from the perspective of informatics.

This research aims to provide a conceptual framework with the scope to assist in establishing sustainable supply chain clusters (SCCs) by providing an instrument for organisations to enhance the three sustainability dimensions in a dynamic environment.

This research proposes a conceptual framework to enhance sustainability and organisational performance through three theoretical lenses: the system theory, extended resource-based view and the dynamic capabilities (DCs) theory. This approach is carried out through a comprehensive review of the existing literature on SCCs.

Four main propositions are formulated and demonstrated using the developed framework, which expands the discussion about SCCs and their key characteristics in a dynamic environment. This is particularly relevant as it allows empirical testing of the theories in an SCC context.

It can be noted that more extensive research is needed to further understand the issues faced in establishing sustainable clusters. Drawing on the theoretical lenses to establish the framework helps to enhance the understanding and operational capabilities of sustainable SCCs during and after disruptions, such as the global disruption created by COVID-19.

This research paves the way to help organisations improve their adaptability to the dynamic business environment by emphasizing the importance of clustering and linking it to sustainability through DCs to establish a sustainable cluster.

This research aims to guide organisations' use of SCCs as tools to enhance sustainability in a dynamic environment, given that the relationship amongst supply chain cluster design characteristics (SCCDCs), DCs and sustainability remains unexplored. The combination of the three theoretical lenses in developing the proposed framework will assist in further understanding the applicability of these theories when they are considered together.

This paper aims to identify and systematically analyze the causal-effect relationships among barriers to circular food supply chains in China.

Grounded in multiple organizational theories, this paper develops a theoretical framework for identifying relevant barriers to integrating circular economy philosophy in food supply chain management. The study uses 105 responses from Chinese food supply chain stakeholders including food processors, sales and distribution channels, consumers and government officials. It applies a fuzzy decision-making trial and evaluation laboratory (DEMATEL) method to examine the causal-effect relationships among the identified barriers.

Overall, the results suggest two key cause barriers: first, weak environmental regulations and enforcement, and second, lack of market preference/pressure. Meanwhile, lack of collaboration/support from supply chain actors is the most prominent barrier. The key cause and prominent barriers are also identified for each of the supply chain stakeholder involved.

The study offers practical insights for overcoming barriers to integrating circular economy philosophy in the management of supply chains in the Chinese food sector, as well as in other contexts where similar challenges are faced. It also sheds light on which organizational theories are most suitable for guiding similar studies.

To the best of the authors’ knowledge, this is the first barrier study on circular food supply chains. The use of multiple organizational theories for the development of the theoretical framework is unique in barrier studies. The study offers insights from multiple stakeholders in the Chinese food supply chains.

The purpose of this paper is to strengthen and standardize general hospital use of traditional Chinese medicine, strengthen the inner construction, highlight the characteristics and advantages of Chinese medicine and improve Chinese medicine services' capacity and competitiveness.

Through data analysis and face‐to‐face interviews, the influential factors for Chinese medicine use in general hospitals are found and the extent and impact of these factors are researched. Based on survey results, grey relational analysis is used to analyze the actual factors.

Based on the results of grey relational analysis, a clear order of these factors on the degree of influence is obtained and suggestions are offered which can promote the development of traditional Chinese medicine in general hospitals.

The grey system theory was applied in medical management. The influential factors for Chinese medicine use in general hospitals was analyzed by using grey relational analysis, to offer the relevant departments several operational recommendations which can accelerate the development of general hospital use of traditional Chinese medicine.